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Related papers: Exploring Prompt Engineering: A Systematic Review …

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This comprehensive review delves into the pivotal role of prompt engineering in unleashing the capabilities of Large Language Models (LLMs). The development of Artificial Intelligence (AI), from its inception in the 1950s to the emergence…

Computation and Language · Computer Science 2025-06-18 Banghao Chen , Zhaofeng Zhang , Nicolas Langrené , Shengxin Zhu

Prompt engineering has emerged as an indispensable technique for extending the capabilities of large language models (LLMs) and vision-language models (VLMs). This approach leverages task-specific instructions, known as prompts, to enhance…

Artificial Intelligence · Computer Science 2025-03-18 Pranab Sahoo , Ayush Kumar Singh , Sriparna Saha , Vinija Jain , Samrat Mondal , Aman Chadha

Large language models (LLMs) have shown remarkable performance on many different Natural Language Processing (NLP) tasks. Prompt engineering plays a key role in adding more to the already existing abilities of LLMs to achieve significant…

Computation and Language · Computer Science 2024-07-25 Shubham Vatsal , Harsh Dubey

Large Language Models (LLMs) have shown prominent performance in various downstream tasks and prompt engineering plays a pivotal role in optimizing LLMs' performance. This paper, not only as an overview of current prompt engineering…

Computation and Language · Computer Science 2024-09-18 Haochen Li , Jonathan Leung , Zhiqi Shen

Generative Artificial Intelligence (GenAI) systems are increasingly being deployed across diverse industries and research domains. Developers and end-users interact with these systems through the use of prompting and prompt engineering.…

Large Language Models (LLMs) have the potential to revolutionize automated traceability by overcoming the challenges faced by previous methods and introducing new possibilities. However, the optimal utilization of LLMs for automated…

Software Engineering · Computer Science 2023-08-02 Alberto D. Rodriguez , Katherine R. Dearstyne , Jane Cleland-Huang

The field of prompt engineering is becoming an essential phenomenon in artificial intelligence. It is altering how data scientists interact with large language models (LLMs) for analytics applications. This research paper shares empirical…

Digital Libraries · Computer Science 2026-02-03 Snehasish Paul , Rohit Kumar , Laxman Das

The rapid advancements in large language models (LLMs) have greatly expanded the potential for automated code-related tasks. Two primary methodologies are used in this domain: prompt engineering and fine-tuning. Prompt engineering involves…

Software Engineering · Computer Science 2025-02-21 Jiho Shin , Clark Tang , Tahmineh Mohati , Maleknaz Nayebi , Song Wang , Hadi Hemmati

Interaction with Large Language Models (LLMs) is primarily carried out via prompting. A prompt is a natural language instruction designed to elicit certain behaviour or output from a model. In theory, natural language prompts enable…

Human-Computer Interaction · Computer Science 2024-03-15 Michael Desmond , Michelle Brachman

While Large Language Models (LLMs) are being quickly adapted to many domains, including healthcare, their strengths and pitfalls remain under-explored. In our study, we examine the effects of prompt engineering to guide Large Language…

Computation and Language · Computer Science 2024-09-04 Daniil Filienko , Yinzhou Wang , Caroline El Jazmi , Serena Xie , Trevor Cohen , Martine De Cock , Weichao Yuwen

The widespread adoption of large language models (LLMs) such as ChatGPT, Gemini, and DeepSeek has significantly changed how people approach tasks in education, professional work, and creative domains. This paper investigates how the…

Human-Computer Interaction · Computer Science 2025-08-29 Rizal Khoirul Anam

Large Language Models (LLMs) have significantly advanced software engineering (SE) tasks, with prompt engineering techniques enhancing their performance in code-related areas. However, the rapid development of foundational LLMs such as the…

Software Engineering · Computer Science 2024-11-05 Guoqing Wang , Zeyu Sun , Zhihao Gong , Sixiang Ye , Yizhou Chen , Yifan Zhao , Qingyuan Liang , Dan Hao

Effective prompt engineering is critical to realizing the promised productivity gains of large language models (LLMs) in knowledge-intensive tasks. Yet, many users struggle to craft prompts that yield high-quality outputs, limiting the…

Human-Computer Interaction · Computer Science 2025-10-02 Niklas Gutheil , Valentin Mayer , Leopold Müller , Jörg Rommelt , Niklas Kühl

Large language models (LLMs) have demonstrated impressive performance across a wide range of Natural Language Processing (NLP) tasks. However, ensuring their effectiveness across multiple languages presents unique challenges. Multilingual…

Computation and Language · Computer Science 2025-05-20 Shubham Vatsal , Harsh Dubey , Aditi Singh

Large language models (LLMs) can perform recommendation tasks by taking prompts written in natural language as input. Compared to traditional methods such as collaborative filtering, LLM-based recommendation offers advantages in handling…

Information Retrieval · Computer Science 2025-07-21 Genki Kusano , Kosuke Akimoto , Kunihiro Takeoka

Recently, large language models (LLMs) have been successfully applied to many fields, showing outstanding comprehension and reasoning capabilities. Despite their great potential, LLMs usually require dedicated pre-training and fine-tuning…

Networking and Internet Architecture · Computer Science 2024-12-31 Hao Zhou , Chengming Hu , Dun Yuan , Ye Yuan , Di Wu , Xi Chen , Hina Tabassum , Xue Liu

Prompt engineering is an increasingly important skill set needed to converse effectively with large language models (LLMs), such as ChatGPT. Prompts are instructions given to an LLM to enforce rules, automate processes, and ensure specific…

Due to rapid advancements in the development of Large Language Models (LLMs), programming these models with prompts has recently gained significant attention. However, the sheer number of available prompt engineering techniques creates an…

Computation and Language · Computer Science 2024-02-26 Oluwole Fagbohun , Rachel M. Harrison , Anton Dereventsov

Large language models (LLMs) have the potential to enhance K-12 STEM education by improving both teaching and learning processes. While previous studies have shown promising results, there is still a lack of comprehensive understanding…

Computation and Language · Computer Science 2024-10-16 Eason Chen , Danyang Wang , Luyi Xu , Chen Cao , Xiao Fang , Jionghao Lin

Prompt design and engineering has rapidly become essential for maximizing the potential of large language models. In this paper, we introduce core concepts, advanced techniques like Chain-of-Thought and Reflection, and the principles behind…

Software Engineering · Computer Science 2024-05-07 Xavier Amatriain
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